利用GNSS PWV的AOD自适应预测方法

doi:10.11947/j.AGCS.2021.20210052

摘要/Abstract

摘要： 气溶胶光学厚度（aerosol optical depth，AOD）是气溶胶总含量的基本参数，对研究大气空气质量变化具有重要作用。为了探究不同类型AOD对空气质量的影响，本文提出两种基于GNSS PWV的AOD自适应预测方法。提出的方法考虑了相邻历元间AOD的时间自相关性，且模型系数能够自适应更新。一种方法是直接基于GNSS PWV对550 nm的AOD进行建模，简称TAF （total AOD forecast）模型。另一种AOD建模方法顾及了5种不同类型AOD对PWV的敏感性，简称FTAF （five type-based AOD forecast，FTAF）模型。该模型首先建立PWV与5种类型AOD的函数关系。其次，依据550 nm AOD与5种类型AOD之间的关系，确定不同类型AOD在550 nm AOD中所占的权重。最后，利用PWV预测5种类型的AOD，并通过加权平均获取最终的550 nm AOD。选取京津冀地区16个GNSS测站数据对提出模型的精度进行验证，结果发现提出的两种550 nm AOD预测模型均具有较高的精度，且FTAF模型优于TAF模型。本文提出的AOD预测模型能有效地将GNSS反演的对流层参数应用于大气环境遥感监测，为大气环境质量研究提供了一种新思路。

关键词: GNSS, PWV, AOD, 预测模型

Abstract: Aerosol optical depth (AOD) is a basic parameter of total aerosol content, which plays an important role in the study of atmospheric air quality. In order to explore the impact of different types of AOD on air quality, this paper proposes two adaptive AOD prediction methods based on GNSS PWV. The proposed method considers the temporal autocorrelation of AOD between adjacent epochs, and the model coefficients can be updated adaptively. One method is to model the 550 nm AOD directly based on GNSS PWV, which is called TAF (total AOD forecast) model. Another AOD modeling method takes into account the sensitivity of five different types of AOD to PWV, referred to it simply as FTAF(five type based AOD forecast) model. The model first establishes the functional relationship between PWV and five types of AOD. Secondly, according to the relationship between 550 nm AOD and five types of AOD, the weight of different types of AOD in 550 nm AOD was determined. Finally, PWV is used to predict five types of AOD, and the final 550 nm AOD is obtained by weighted average. 16 GNSS stations in Beijing, Tianjin, Hebei region are selected to verify the accuracy of the proposed model. The results show that the two 550 nm AOD prediction models have high accuracy, and the FTAF model is better than the TAF model. The AOD prediction model proposed in this paper can effectively apply the tropospheric parameters retrieved from GNSS to remote sensing monitoring of atmospheric environment, which provides a new idea for the study of atmospheric environmental quality.

Key words: GNSS, PWV, AOD, prediction model

中图分类号:

P288

赵庆志, 苏静, 杨鹏飞, 姚宜斌. 利用GNSS PWV的AOD自适应预测方法[J]. 测绘学报, 2021, 50(10): 1279-1289.

ZHAO Qingzhi, SU Jing, YANG Pengfei, YAO Yibin. AOD adaptive prediction method based on GNSS PWV[J]. Acta Geodaetica et Cartographica Sinica, 2021, 50(10): 1279-1289.

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